Data.Colour.Matrix:determinant from colour-2.3.3, A

Percentage Accurate: 73.8% → 83.6%

Time: 32.2s

Alternatives: 27

Speedup: 0.5×

• 57.4% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(x \cdot \left(y \cdot z - t \cdot a\right) - b \cdot \left(c \cdot z - t \cdot i\right)\right) + j \cdot \left(c \cdot a - y \cdot i\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (+
  (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* t i))))
  (* j (- (* c a) (* y i)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    code = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
}

Python

def code(x, y, z, t, a, b, c, i, j):
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)))

Julia

function code(x, y, z, t, a, b, c, i, j)
	return Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(b * Float64(Float64(c * z) - Float64(t * i)))) + Float64(j * Float64(Float64(c * a) - Float64(y * i))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(c * z), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(c * a), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Initial Program: 73.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(x \cdot \left(y \cdot z - t \cdot a\right) - b \cdot \left(c \cdot z - t \cdot i\right)\right) + j \cdot \left(c \cdot a - y \cdot i\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (+
  (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* t i))))
  (* j (- (* c a) (* y i)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    code = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
}

Python

def code(x, y, z, t, a, b, c, i, j):
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)))

Julia

function code(x, y, z, t, a, b, c, i, j)
	return Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(b * Float64(Float64(c * z) - Float64(t * i)))) + Float64(j * Float64(Float64(c * a) - Float64(y * i))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(c * z), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(c * a), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Alternative 1: 83.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(x \cdot \left(y \cdot z - t \cdot a\right) + b \cdot \left(t \cdot i - z \cdot c\right)\right) + j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;t_1 \leq \infty:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right) + a \cdot \left(c \cdot j - x \cdot t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1
         (+
          (+ (* x (- (* y z) (* t a))) (* b (- (* t i) (* z c))))
          (* j (- (* a c) (* y i))))))
   (if (<= t_1 INFINITY)
     t_1
     (+ (* y (- (* x z) (* i j))) (* a (- (* c j) (* x t)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))) + (j * ((a * c) - (y * i)));
	double tmp;
	if (t_1 <= ((double) INFINITY)) {
		tmp = t_1;
	} else {
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)));
	}
	return tmp;
}

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))) + (j * ((a * c) - (y * i)));
	double tmp;
	if (t_1 <= Double.POSITIVE_INFINITY) {
		tmp = t_1;
	} else {
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = ((x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))) + (j * ((a * c) - (y * i)))
	tmp = 0
	if t_1 <= math.inf:
		tmp = t_1
	else:
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(t * i) - Float64(z * c)))) + Float64(j * Float64(Float64(a * c) - Float64(y * i))))
	tmp = 0.0
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) + Float64(a * Float64(Float64(c * j) - Float64(x * t))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = ((x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))) + (j * ((a * c) - (y * i)));
	tmp = 0.0;
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, Infinity], t$95$1, N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 2: 49.7% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \left(x \cdot y - b \cdot c\right)\\ t_2 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_3 := i \cdot \left(t \cdot b - y \cdot j\right)\\ t_4 := j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -1.4 \cdot 10^{-58}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;j \leq 4.2 \cdot 10^{-248}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 2.35 \cdot 10^{-120}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 3.9 \cdot 10^{-104}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 1.25 \cdot 10^{+104}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 9 \cdot 10^{+184}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;j \leq 1.4 \cdot 10^{+185}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 2.85 \cdot 10^{+262}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t_4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* z (- (* x y) (* b c))))
        (t_2 (* x (- (* y z) (* t a))))
        (t_3 (* i (- (* t b) (* y j))))
        (t_4 (* j (- (* a c) (* y i)))))
   (if (<= j -1.4e-58)
     t_4
     (if (<= j 4.2e-248)
       t_2
       (if (<= j 2.35e-120)
         t_1
         (if (<= j 3.9e-104)
           t_3
           (if (<= j 1.25e+104)
             t_2
             (if (<= j 9e+184)
               t_4
               (if (<= j 1.4e+185) t_1 (if (<= j 2.85e+262) t_3 t_4))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = z * ((x * y) - (b * c));
	double t_2 = x * ((y * z) - (t * a));
	double t_3 = i * ((t * b) - (y * j));
	double t_4 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -1.4e-58) {
		tmp = t_4;
	} else if (j <= 4.2e-248) {
		tmp = t_2;
	} else if (j <= 2.35e-120) {
		tmp = t_1;
	} else if (j <= 3.9e-104) {
		tmp = t_3;
	} else if (j <= 1.25e+104) {
		tmp = t_2;
	} else if (j <= 9e+184) {
		tmp = t_4;
	} else if (j <= 1.4e+185) {
		tmp = t_1;
	} else if (j <= 2.85e+262) {
		tmp = t_3;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = z * ((x * y) - (b * c))
    t_2 = x * ((y * z) - (t * a))
    t_3 = i * ((t * b) - (y * j))
    t_4 = j * ((a * c) - (y * i))
    if (j <= (-1.4d-58)) then
        tmp = t_4
    else if (j <= 4.2d-248) then
        tmp = t_2
    else if (j <= 2.35d-120) then
        tmp = t_1
    else if (j <= 3.9d-104) then
        tmp = t_3
    else if (j <= 1.25d+104) then
        tmp = t_2
    else if (j <= 9d+184) then
        tmp = t_4
    else if (j <= 1.4d+185) then
        tmp = t_1
    else if (j <= 2.85d+262) then
        tmp = t_3
    else
        tmp = t_4
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = z * ((x * y) - (b * c));
	double t_2 = x * ((y * z) - (t * a));
	double t_3 = i * ((t * b) - (y * j));
	double t_4 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -1.4e-58) {
		tmp = t_4;
	} else if (j <= 4.2e-248) {
		tmp = t_2;
	} else if (j <= 2.35e-120) {
		tmp = t_1;
	} else if (j <= 3.9e-104) {
		tmp = t_3;
	} else if (j <= 1.25e+104) {
		tmp = t_2;
	} else if (j <= 9e+184) {
		tmp = t_4;
	} else if (j <= 1.4e+185) {
		tmp = t_1;
	} else if (j <= 2.85e+262) {
		tmp = t_3;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = z * ((x * y) - (b * c))
	t_2 = x * ((y * z) - (t * a))
	t_3 = i * ((t * b) - (y * j))
	t_4 = j * ((a * c) - (y * i))
	tmp = 0
	if j <= -1.4e-58:
		tmp = t_4
	elif j <= 4.2e-248:
		tmp = t_2
	elif j <= 2.35e-120:
		tmp = t_1
	elif j <= 3.9e-104:
		tmp = t_3
	elif j <= 1.25e+104:
		tmp = t_2
	elif j <= 9e+184:
		tmp = t_4
	elif j <= 1.4e+185:
		tmp = t_1
	elif j <= 2.85e+262:
		tmp = t_3
	else:
		tmp = t_4
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(z * Float64(Float64(x * y) - Float64(b * c)))
	t_2 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	t_3 = Float64(i * Float64(Float64(t * b) - Float64(y * j)))
	t_4 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -1.4e-58)
		tmp = t_4;
	elseif (j <= 4.2e-248)
		tmp = t_2;
	elseif (j <= 2.35e-120)
		tmp = t_1;
	elseif (j <= 3.9e-104)
		tmp = t_3;
	elseif (j <= 1.25e+104)
		tmp = t_2;
	elseif (j <= 9e+184)
		tmp = t_4;
	elseif (j <= 1.4e+185)
		tmp = t_1;
	elseif (j <= 2.85e+262)
		tmp = t_3;
	else
		tmp = t_4;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = z * ((x * y) - (b * c));
	t_2 = x * ((y * z) - (t * a));
	t_3 = i * ((t * b) - (y * j));
	t_4 = j * ((a * c) - (y * i));
	tmp = 0.0;
	if (j <= -1.4e-58)
		tmp = t_4;
	elseif (j <= 4.2e-248)
		tmp = t_2;
	elseif (j <= 2.35e-120)
		tmp = t_1;
	elseif (j <= 3.9e-104)
		tmp = t_3;
	elseif (j <= 1.25e+104)
		tmp = t_2;
	elseif (j <= 9e+184)
		tmp = t_4;
	elseif (j <= 1.4e+185)
		tmp = t_1;
	elseif (j <= 2.85e+262)
		tmp = t_3;
	else
		tmp = t_4;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(z * N[(N[(x * y), $MachinePrecision] - N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.4e-58], t$95$4, If[LessEqual[j, 4.2e-248], t$95$2, If[LessEqual[j, 2.35e-120], t$95$1, If[LessEqual[j, 3.9e-104], t$95$3, If[LessEqual[j, 1.25e+104], t$95$2, If[LessEqual[j, 9e+184], t$95$4, If[LessEqual[j, 1.4e+185], t$95$1, If[LessEqual[j, 2.85e+262], t$95$3, t$95$4]]]]]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 3: 66.7% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(a \cdot c - y \cdot i\right)\\ t_2 := x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{if}\;i \leq -6.8 \cdot 10^{+103}:\\ \;\;\;\;t \cdot \left(b \cdot i\right) + t_1\\ \mathbf{elif}\;i \leq 3.2 \cdot 10^{-33}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right) + t_2\\ \mathbf{elif}\;i \leq 7 \cdot 10^{+177}:\\ \;\;\;\;t_2 + t_1\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(t \cdot b - y \cdot j\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* a c) (* y i)))) (t_2 (* x (- (* y z) (* t a)))))
   (if (<= i -6.8e+103)
     (+ (* t (* b i)) t_1)
     (if (<= i 3.2e-33)
       (+ (* c (- (* a j) (* z b))) t_2)
       (if (<= i 7e+177) (+ t_2 t_1) (* i (- (* t b) (* y j))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double t_2 = x * ((y * z) - (t * a));
	double tmp;
	if (i <= -6.8e+103) {
		tmp = (t * (b * i)) + t_1;
	} else if (i <= 3.2e-33) {
		tmp = (c * ((a * j) - (z * b))) + t_2;
	} else if (i <= 7e+177) {
		tmp = t_2 + t_1;
	} else {
		tmp = i * ((t * b) - (y * j));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * ((a * c) - (y * i))
    t_2 = x * ((y * z) - (t * a))
    if (i <= (-6.8d+103)) then
        tmp = (t * (b * i)) + t_1
    else if (i <= 3.2d-33) then
        tmp = (c * ((a * j) - (z * b))) + t_2
    else if (i <= 7d+177) then
        tmp = t_2 + t_1
    else
        tmp = i * ((t * b) - (y * j))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double t_2 = x * ((y * z) - (t * a));
	double tmp;
	if (i <= -6.8e+103) {
		tmp = (t * (b * i)) + t_1;
	} else if (i <= 3.2e-33) {
		tmp = (c * ((a * j) - (z * b))) + t_2;
	} else if (i <= 7e+177) {
		tmp = t_2 + t_1;
	} else {
		tmp = i * ((t * b) - (y * j));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((a * c) - (y * i))
	t_2 = x * ((y * z) - (t * a))
	tmp = 0
	if i <= -6.8e+103:
		tmp = (t * (b * i)) + t_1
	elif i <= 3.2e-33:
		tmp = (c * ((a * j) - (z * b))) + t_2
	elif i <= 7e+177:
		tmp = t_2 + t_1
	else:
		tmp = i * ((t * b) - (y * j))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	t_2 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	tmp = 0.0
	if (i <= -6.8e+103)
		tmp = Float64(Float64(t * Float64(b * i)) + t_1);
	elseif (i <= 3.2e-33)
		tmp = Float64(Float64(c * Float64(Float64(a * j) - Float64(z * b))) + t_2);
	elseif (i <= 7e+177)
		tmp = Float64(t_2 + t_1);
	else
		tmp = Float64(i * Float64(Float64(t * b) - Float64(y * j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((a * c) - (y * i));
	t_2 = x * ((y * z) - (t * a));
	tmp = 0.0;
	if (i <= -6.8e+103)
		tmp = (t * (b * i)) + t_1;
	elseif (i <= 3.2e-33)
		tmp = (c * ((a * j) - (z * b))) + t_2;
	elseif (i <= 7e+177)
		tmp = t_2 + t_1;
	else
		tmp = i * ((t * b) - (y * j));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -6.8e+103], N[(N[(t * N[(b * i), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[i, 3.2e-33], N[(N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision], If[LessEqual[i, 7e+177], N[(t$95$2 + t$95$1), $MachinePrecision], N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 4: 66.6% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -1.1 \cdot 10^{+105}:\\ \;\;\;\;t \cdot \left(b \cdot i\right) + j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{elif}\;i \leq 6.8 \cdot 10^{+17}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right) + x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{elif}\;i \leq 7.5 \cdot 10^{+177}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right) + a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(t \cdot b - y \cdot j\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= i -1.1e+105)
   (+ (* t (* b i)) (* j (- (* a c) (* y i))))
   (if (<= i 6.8e+17)
     (+ (* c (- (* a j) (* z b))) (* x (- (* y z) (* t a))))
     (if (<= i 7.5e+177)
       (+ (* y (- (* x z) (* i j))) (* a (- (* c j) (* x t))))
       (* i (- (* t b) (* y j)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (i <= -1.1e+105) {
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	} else if (i <= 6.8e+17) {
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	} else if (i <= 7.5e+177) {
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)));
	} else {
		tmp = i * ((t * b) - (y * j));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (i <= (-1.1d+105)) then
        tmp = (t * (b * i)) + (j * ((a * c) - (y * i)))
    else if (i <= 6.8d+17) then
        tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)))
    else if (i <= 7.5d+177) then
        tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)))
    else
        tmp = i * ((t * b) - (y * j))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (i <= -1.1e+105) {
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	} else if (i <= 6.8e+17) {
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	} else if (i <= 7.5e+177) {
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)));
	} else {
		tmp = i * ((t * b) - (y * j));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if i <= -1.1e+105:
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)))
	elif i <= 6.8e+17:
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)))
	elif i <= 7.5e+177:
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)))
	else:
		tmp = i * ((t * b) - (y * j))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (i <= -1.1e+105)
		tmp = Float64(Float64(t * Float64(b * i)) + Float64(j * Float64(Float64(a * c) - Float64(y * i))));
	elseif (i <= 6.8e+17)
		tmp = Float64(Float64(c * Float64(Float64(a * j) - Float64(z * b))) + Float64(x * Float64(Float64(y * z) - Float64(t * a))));
	elseif (i <= 7.5e+177)
		tmp = Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) + Float64(a * Float64(Float64(c * j) - Float64(x * t))));
	else
		tmp = Float64(i * Float64(Float64(t * b) - Float64(y * j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (i <= -1.1e+105)
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	elseif (i <= 6.8e+17)
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	elseif (i <= 7.5e+177)
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)));
	else
		tmp = i * ((t * b) - (y * j));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[i, -1.1e+105], N[(N[(t * N[(b * i), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 6.8e+17], N[(N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 7.5e+177], N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 5: 65.9% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -2.1 \cdot 10^{+103}:\\ \;\;\;\;t \cdot \left(b \cdot i\right) + j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{elif}\;i \leq 4.6 \cdot 10^{+26}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right) + x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{elif}\;i \leq 7 \cdot 10^{+177}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right) - a \cdot \left(x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(t \cdot b - y \cdot j\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= i -2.1e+103)
   (+ (* t (* b i)) (* j (- (* a c) (* y i))))
   (if (<= i 4.6e+26)
     (+ (* c (- (* a j) (* z b))) (* x (- (* y z) (* t a))))
     (if (<= i 7e+177)
       (- (* y (- (* x z) (* i j))) (* a (* x t)))
       (* i (- (* t b) (* y j)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (i <= -2.1e+103) {
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	} else if (i <= 4.6e+26) {
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	} else if (i <= 7e+177) {
		tmp = (y * ((x * z) - (i * j))) - (a * (x * t));
	} else {
		tmp = i * ((t * b) - (y * j));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (i <= (-2.1d+103)) then
        tmp = (t * (b * i)) + (j * ((a * c) - (y * i)))
    else if (i <= 4.6d+26) then
        tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)))
    else if (i <= 7d+177) then
        tmp = (y * ((x * z) - (i * j))) - (a * (x * t))
    else
        tmp = i * ((t * b) - (y * j))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (i <= -2.1e+103) {
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	} else if (i <= 4.6e+26) {
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	} else if (i <= 7e+177) {
		tmp = (y * ((x * z) - (i * j))) - (a * (x * t));
	} else {
		tmp = i * ((t * b) - (y * j));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if i <= -2.1e+103:
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)))
	elif i <= 4.6e+26:
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)))
	elif i <= 7e+177:
		tmp = (y * ((x * z) - (i * j))) - (a * (x * t))
	else:
		tmp = i * ((t * b) - (y * j))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (i <= -2.1e+103)
		tmp = Float64(Float64(t * Float64(b * i)) + Float64(j * Float64(Float64(a * c) - Float64(y * i))));
	elseif (i <= 4.6e+26)
		tmp = Float64(Float64(c * Float64(Float64(a * j) - Float64(z * b))) + Float64(x * Float64(Float64(y * z) - Float64(t * a))));
	elseif (i <= 7e+177)
		tmp = Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) - Float64(a * Float64(x * t)));
	else
		tmp = Float64(i * Float64(Float64(t * b) - Float64(y * j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (i <= -2.1e+103)
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	elseif (i <= 4.6e+26)
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	elseif (i <= 7e+177)
		tmp = (y * ((x * z) - (i * j))) - (a * (x * t));
	else
		tmp = i * ((t * b) - (y * j));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[i, -2.1e+103], N[(N[(t * N[(b * i), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 4.6e+26], N[(N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 7e+177], N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 6: 67.0% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;i \leq -1.1 \cdot 10^{+105}:\\ \;\;\;\;t \cdot \left(b \cdot i\right) + t_1\\ \mathbf{elif}\;i \leq 3 \cdot 10^{-19}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right) + x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;t_1 - t \cdot \left(x \cdot a - b \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* a c) (* y i)))))
   (if (<= i -1.1e+105)
     (+ (* t (* b i)) t_1)
     (if (<= i 3e-19)
       (+ (* c (- (* a j) (* z b))) (* x (- (* y z) (* t a))))
       (- t_1 (* t (- (* x a) (* b i))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double tmp;
	if (i <= -1.1e+105) {
		tmp = (t * (b * i)) + t_1;
	} else if (i <= 3e-19) {
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	} else {
		tmp = t_1 - (t * ((x * a) - (b * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * ((a * c) - (y * i))
    if (i <= (-1.1d+105)) then
        tmp = (t * (b * i)) + t_1
    else if (i <= 3d-19) then
        tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)))
    else
        tmp = t_1 - (t * ((x * a) - (b * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double tmp;
	if (i <= -1.1e+105) {
		tmp = (t * (b * i)) + t_1;
	} else if (i <= 3e-19) {
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	} else {
		tmp = t_1 - (t * ((x * a) - (b * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((a * c) - (y * i))
	tmp = 0
	if i <= -1.1e+105:
		tmp = (t * (b * i)) + t_1
	elif i <= 3e-19:
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)))
	else:
		tmp = t_1 - (t * ((x * a) - (b * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	tmp = 0.0
	if (i <= -1.1e+105)
		tmp = Float64(Float64(t * Float64(b * i)) + t_1);
	elseif (i <= 3e-19)
		tmp = Float64(Float64(c * Float64(Float64(a * j) - Float64(z * b))) + Float64(x * Float64(Float64(y * z) - Float64(t * a))));
	else
		tmp = Float64(t_1 - Float64(t * Float64(Float64(x * a) - Float64(b * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((a * c) - (y * i));
	tmp = 0.0;
	if (i <= -1.1e+105)
		tmp = (t * (b * i)) + t_1;
	elseif (i <= 3e-19)
		tmp = (c * ((a * j) - (z * b))) + (x * ((y * z) - (t * a)));
	else
		tmp = t_1 - (t * ((x * a) - (b * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -1.1e+105], N[(N[(t * N[(b * i), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[i, 3e-19], N[(N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t$95$1 - N[(t * N[(N[(x * a), $MachinePrecision] - N[(b * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 7: 29.6% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(a \cdot j\right)\\ \mathbf{if}\;j \leq -4.9 \cdot 10^{+184}:\\ \;\;\;\;y \cdot \left(j \cdot \left(-i\right)\right)\\ \mathbf{elif}\;j \leq -3.6 \cdot 10^{-11}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -1.15 \cdot 10^{-124}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(-x\right)\\ \mathbf{elif}\;j \leq -1.25 \cdot 10^{-199}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \mathbf{elif}\;j \leq -1.22 \cdot 10^{-206}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{elif}\;j \leq 7.5 \cdot 10^{-195}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \mathbf{elif}\;j \leq 4.2 \cdot 10^{-141}:\\ \;\;\;\;\left(b \cdot c\right) \cdot \left(-z\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{+97}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (* a j))))
   (if (<= j -4.9e+184)
     (* y (* j (- i)))
     (if (<= j -3.6e-11)
       t_1
       (if (<= j -1.15e-124)
         (* (* t a) (- x))
         (if (<= j -1.25e-199)
           (* c (* z (- b)))
           (if (<= j -1.22e-206)
             (* a (* x (- t)))
             (if (<= j 7.5e-195)
               (* y (* x z))
               (if (<= j 4.2e-141)
                 (* (* b c) (- z))
                 (if (<= j 1.7e+97) (* x (* y z)) t_1))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -4.9e+184) {
		tmp = y * (j * -i);
	} else if (j <= -3.6e-11) {
		tmp = t_1;
	} else if (j <= -1.15e-124) {
		tmp = (t * a) * -x;
	} else if (j <= -1.25e-199) {
		tmp = c * (z * -b);
	} else if (j <= -1.22e-206) {
		tmp = a * (x * -t);
	} else if (j <= 7.5e-195) {
		tmp = y * (x * z);
	} else if (j <= 4.2e-141) {
		tmp = (b * c) * -z;
	} else if (j <= 1.7e+97) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (a * j)
    if (j <= (-4.9d+184)) then
        tmp = y * (j * -i)
    else if (j <= (-3.6d-11)) then
        tmp = t_1
    else if (j <= (-1.15d-124)) then
        tmp = (t * a) * -x
    else if (j <= (-1.25d-199)) then
        tmp = c * (z * -b)
    else if (j <= (-1.22d-206)) then
        tmp = a * (x * -t)
    else if (j <= 7.5d-195) then
        tmp = y * (x * z)
    else if (j <= 4.2d-141) then
        tmp = (b * c) * -z
    else if (j <= 1.7d+97) then
        tmp = x * (y * z)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -4.9e+184) {
		tmp = y * (j * -i);
	} else if (j <= -3.6e-11) {
		tmp = t_1;
	} else if (j <= -1.15e-124) {
		tmp = (t * a) * -x;
	} else if (j <= -1.25e-199) {
		tmp = c * (z * -b);
	} else if (j <= -1.22e-206) {
		tmp = a * (x * -t);
	} else if (j <= 7.5e-195) {
		tmp = y * (x * z);
	} else if (j <= 4.2e-141) {
		tmp = (b * c) * -z;
	} else if (j <= 1.7e+97) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * (a * j)
	tmp = 0
	if j <= -4.9e+184:
		tmp = y * (j * -i)
	elif j <= -3.6e-11:
		tmp = t_1
	elif j <= -1.15e-124:
		tmp = (t * a) * -x
	elif j <= -1.25e-199:
		tmp = c * (z * -b)
	elif j <= -1.22e-206:
		tmp = a * (x * -t)
	elif j <= 7.5e-195:
		tmp = y * (x * z)
	elif j <= 4.2e-141:
		tmp = (b * c) * -z
	elif j <= 1.7e+97:
		tmp = x * (y * z)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(a * j))
	tmp = 0.0
	if (j <= -4.9e+184)
		tmp = Float64(y * Float64(j * Float64(-i)));
	elseif (j <= -3.6e-11)
		tmp = t_1;
	elseif (j <= -1.15e-124)
		tmp = Float64(Float64(t * a) * Float64(-x));
	elseif (j <= -1.25e-199)
		tmp = Float64(c * Float64(z * Float64(-b)));
	elseif (j <= -1.22e-206)
		tmp = Float64(a * Float64(x * Float64(-t)));
	elseif (j <= 7.5e-195)
		tmp = Float64(y * Float64(x * z));
	elseif (j <= 4.2e-141)
		tmp = Float64(Float64(b * c) * Float64(-z));
	elseif (j <= 1.7e+97)
		tmp = Float64(x * Float64(y * z));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * (a * j);
	tmp = 0.0;
	if (j <= -4.9e+184)
		tmp = y * (j * -i);
	elseif (j <= -3.6e-11)
		tmp = t_1;
	elseif (j <= -1.15e-124)
		tmp = (t * a) * -x;
	elseif (j <= -1.25e-199)
		tmp = c * (z * -b);
	elseif (j <= -1.22e-206)
		tmp = a * (x * -t);
	elseif (j <= 7.5e-195)
		tmp = y * (x * z);
	elseif (j <= 4.2e-141)
		tmp = (b * c) * -z;
	elseif (j <= 1.7e+97)
		tmp = x * (y * z);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -4.9e+184], N[(y * N[(j * (-i)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -3.6e-11], t$95$1, If[LessEqual[j, -1.15e-124], N[(N[(t * a), $MachinePrecision] * (-x)), $MachinePrecision], If[LessEqual[j, -1.25e-199], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.22e-206], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7.5e-195], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.2e-141], N[(N[(b * c), $MachinePrecision] * (-z)), $MachinePrecision], If[LessEqual[j, 1.7e+97], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 8: 29.6% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(a \cdot j\right)\\ \mathbf{if}\;j \leq -2.3 \cdot 10^{+181}:\\ \;\;\;\;y \cdot \left(j \cdot \left(-i\right)\right)\\ \mathbf{elif}\;j \leq -5.4 \cdot 10^{-11}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{-125}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(-x\right)\\ \mathbf{elif}\;j \leq -1.35 \cdot 10^{-199}:\\ \;\;\;\;b \cdot \left(c \cdot \left(-z\right)\right)\\ \mathbf{elif}\;j \leq -5.6 \cdot 10^{-200}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{elif}\;j \leq 3.5 \cdot 10^{-194}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \mathbf{elif}\;j \leq 6.1 \cdot 10^{-144}:\\ \;\;\;\;\left(b \cdot c\right) \cdot \left(-z\right)\\ \mathbf{elif}\;j \leq 8.5 \cdot 10^{+100}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (* a j))))
   (if (<= j -2.3e+181)
     (* y (* j (- i)))
     (if (<= j -5.4e-11)
       t_1
       (if (<= j -8.5e-125)
         (* (* t a) (- x))
         (if (<= j -1.35e-199)
           (* b (* c (- z)))
           (if (<= j -5.6e-200)
             (* a (* x (- t)))
             (if (<= j 3.5e-194)
               (* y (* x z))
               (if (<= j 6.1e-144)
                 (* (* b c) (- z))
                 (if (<= j 8.5e+100) (* x (* y z)) t_1))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -2.3e+181) {
		tmp = y * (j * -i);
	} else if (j <= -5.4e-11) {
		tmp = t_1;
	} else if (j <= -8.5e-125) {
		tmp = (t * a) * -x;
	} else if (j <= -1.35e-199) {
		tmp = b * (c * -z);
	} else if (j <= -5.6e-200) {
		tmp = a * (x * -t);
	} else if (j <= 3.5e-194) {
		tmp = y * (x * z);
	} else if (j <= 6.1e-144) {
		tmp = (b * c) * -z;
	} else if (j <= 8.5e+100) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (a * j)
    if (j <= (-2.3d+181)) then
        tmp = y * (j * -i)
    else if (j <= (-5.4d-11)) then
        tmp = t_1
    else if (j <= (-8.5d-125)) then
        tmp = (t * a) * -x
    else if (j <= (-1.35d-199)) then
        tmp = b * (c * -z)
    else if (j <= (-5.6d-200)) then
        tmp = a * (x * -t)
    else if (j <= 3.5d-194) then
        tmp = y * (x * z)
    else if (j <= 6.1d-144) then
        tmp = (b * c) * -z
    else if (j <= 8.5d+100) then
        tmp = x * (y * z)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -2.3e+181) {
		tmp = y * (j * -i);
	} else if (j <= -5.4e-11) {
		tmp = t_1;
	} else if (j <= -8.5e-125) {
		tmp = (t * a) * -x;
	} else if (j <= -1.35e-199) {
		tmp = b * (c * -z);
	} else if (j <= -5.6e-200) {
		tmp = a * (x * -t);
	} else if (j <= 3.5e-194) {
		tmp = y * (x * z);
	} else if (j <= 6.1e-144) {
		tmp = (b * c) * -z;
	} else if (j <= 8.5e+100) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * (a * j)
	tmp = 0
	if j <= -2.3e+181:
		tmp = y * (j * -i)
	elif j <= -5.4e-11:
		tmp = t_1
	elif j <= -8.5e-125:
		tmp = (t * a) * -x
	elif j <= -1.35e-199:
		tmp = b * (c * -z)
	elif j <= -5.6e-200:
		tmp = a * (x * -t)
	elif j <= 3.5e-194:
		tmp = y * (x * z)
	elif j <= 6.1e-144:
		tmp = (b * c) * -z
	elif j <= 8.5e+100:
		tmp = x * (y * z)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(a * j))
	tmp = 0.0
	if (j <= -2.3e+181)
		tmp = Float64(y * Float64(j * Float64(-i)));
	elseif (j <= -5.4e-11)
		tmp = t_1;
	elseif (j <= -8.5e-125)
		tmp = Float64(Float64(t * a) * Float64(-x));
	elseif (j <= -1.35e-199)
		tmp = Float64(b * Float64(c * Float64(-z)));
	elseif (j <= -5.6e-200)
		tmp = Float64(a * Float64(x * Float64(-t)));
	elseif (j <= 3.5e-194)
		tmp = Float64(y * Float64(x * z));
	elseif (j <= 6.1e-144)
		tmp = Float64(Float64(b * c) * Float64(-z));
	elseif (j <= 8.5e+100)
		tmp = Float64(x * Float64(y * z));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * (a * j);
	tmp = 0.0;
	if (j <= -2.3e+181)
		tmp = y * (j * -i);
	elseif (j <= -5.4e-11)
		tmp = t_1;
	elseif (j <= -8.5e-125)
		tmp = (t * a) * -x;
	elseif (j <= -1.35e-199)
		tmp = b * (c * -z);
	elseif (j <= -5.6e-200)
		tmp = a * (x * -t);
	elseif (j <= 3.5e-194)
		tmp = y * (x * z);
	elseif (j <= 6.1e-144)
		tmp = (b * c) * -z;
	elseif (j <= 8.5e+100)
		tmp = x * (y * z);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.3e+181], N[(y * N[(j * (-i)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -5.4e-11], t$95$1, If[LessEqual[j, -8.5e-125], N[(N[(t * a), $MachinePrecision] * (-x)), $MachinePrecision], If[LessEqual[j, -1.35e-199], N[(b * N[(c * (-z)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -5.6e-200], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.5e-194], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.1e-144], N[(N[(b * c), $MachinePrecision] * (-z)), $MachinePrecision], If[LessEqual[j, 8.5e+100], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 9: 51.4% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := t \cdot \left(b \cdot i - x \cdot a\right)\\ t_3 := j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -2.9 \cdot 10^{-57}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 1.15 \cdot 10^{-247}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 4.1 \cdot 10^{-122}:\\ \;\;\;\;z \cdot \left(x \cdot y - b \cdot c\right)\\ \mathbf{elif}\;j \leq 1.4 \cdot 10^{-104}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 2.8 \cdot 10^{-18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 5.5 \cdot 10^{+103}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a))))
        (t_2 (* t (- (* b i) (* x a))))
        (t_3 (* j (- (* a c) (* y i)))))
   (if (<= j -2.9e-57)
     t_3
     (if (<= j 1.15e-247)
       t_1
       (if (<= j 4.1e-122)
         (* z (- (* x y) (* b c)))
         (if (<= j 1.4e-104)
           t_2
           (if (<= j 2.8e-18) t_1 (if (<= j 5.5e+103) t_2 t_3))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = t * ((b * i) - (x * a));
	double t_3 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -2.9e-57) {
		tmp = t_3;
	} else if (j <= 1.15e-247) {
		tmp = t_1;
	} else if (j <= 4.1e-122) {
		tmp = z * ((x * y) - (b * c));
	} else if (j <= 1.4e-104) {
		tmp = t_2;
	} else if (j <= 2.8e-18) {
		tmp = t_1;
	} else if (j <= 5.5e+103) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = x * ((y * z) - (t * a))
    t_2 = t * ((b * i) - (x * a))
    t_3 = j * ((a * c) - (y * i))
    if (j <= (-2.9d-57)) then
        tmp = t_3
    else if (j <= 1.15d-247) then
        tmp = t_1
    else if (j <= 4.1d-122) then
        tmp = z * ((x * y) - (b * c))
    else if (j <= 1.4d-104) then
        tmp = t_2
    else if (j <= 2.8d-18) then
        tmp = t_1
    else if (j <= 5.5d+103) then
        tmp = t_2
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = t * ((b * i) - (x * a));
	double t_3 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -2.9e-57) {
		tmp = t_3;
	} else if (j <= 1.15e-247) {
		tmp = t_1;
	} else if (j <= 4.1e-122) {
		tmp = z * ((x * y) - (b * c));
	} else if (j <= 1.4e-104) {
		tmp = t_2;
	} else if (j <= 2.8e-18) {
		tmp = t_1;
	} else if (j <= 5.5e+103) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * ((y * z) - (t * a))
	t_2 = t * ((b * i) - (x * a))
	t_3 = j * ((a * c) - (y * i))
	tmp = 0
	if j <= -2.9e-57:
		tmp = t_3
	elif j <= 1.15e-247:
		tmp = t_1
	elif j <= 4.1e-122:
		tmp = z * ((x * y) - (b * c))
	elif j <= 1.4e-104:
		tmp = t_2
	elif j <= 2.8e-18:
		tmp = t_1
	elif j <= 5.5e+103:
		tmp = t_2
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	t_2 = Float64(t * Float64(Float64(b * i) - Float64(x * a)))
	t_3 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -2.9e-57)
		tmp = t_3;
	elseif (j <= 1.15e-247)
		tmp = t_1;
	elseif (j <= 4.1e-122)
		tmp = Float64(z * Float64(Float64(x * y) - Float64(b * c)));
	elseif (j <= 1.4e-104)
		tmp = t_2;
	elseif (j <= 2.8e-18)
		tmp = t_1;
	elseif (j <= 5.5e+103)
		tmp = t_2;
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((y * z) - (t * a));
	t_2 = t * ((b * i) - (x * a));
	t_3 = j * ((a * c) - (y * i));
	tmp = 0.0;
	if (j <= -2.9e-57)
		tmp = t_3;
	elseif (j <= 1.15e-247)
		tmp = t_1;
	elseif (j <= 4.1e-122)
		tmp = z * ((x * y) - (b * c));
	elseif (j <= 1.4e-104)
		tmp = t_2;
	elseif (j <= 2.8e-18)
		tmp = t_1;
	elseif (j <= 5.5e+103)
		tmp = t_2;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(b * i), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.9e-57], t$95$3, If[LessEqual[j, 1.15e-247], t$95$1, If[LessEqual[j, 4.1e-122], N[(z * N[(N[(x * y), $MachinePrecision] - N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.4e-104], t$95$2, If[LessEqual[j, 2.8e-18], t$95$1, If[LessEqual[j, 5.5e+103], t$95$2, t$95$3]]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 10: 55.4% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(a \cdot c - y \cdot i\right)\\ t_2 := x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{if}\;x \leq -3.9 \cdot 10^{+50}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x \leq -3.5 \cdot 10^{-303}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{elif}\;x \leq 1.1 \cdot 10^{+40}:\\ \;\;\;\;t_1 + b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;x \leq 1.1 \cdot 10^{+109} \lor \neg \left(x \leq 3.1 \cdot 10^{+146}\right):\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* a c) (* y i)))) (t_2 (* x (- (* y z) (* t a)))))
   (if (<= x -3.9e+50)
     t_2
     (if (<= x -3.5e-303)
       (* c (- (* a j) (* z b)))
       (if (<= x 1.1e+40)
         (+ t_1 (* b (* t i)))
         (if (or (<= x 1.1e+109) (not (<= x 3.1e+146))) t_2 t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double t_2 = x * ((y * z) - (t * a));
	double tmp;
	if (x <= -3.9e+50) {
		tmp = t_2;
	} else if (x <= -3.5e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 1.1e+40) {
		tmp = t_1 + (b * (t * i));
	} else if ((x <= 1.1e+109) || !(x <= 3.1e+146)) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * ((a * c) - (y * i))
    t_2 = x * ((y * z) - (t * a))
    if (x <= (-3.9d+50)) then
        tmp = t_2
    else if (x <= (-3.5d-303)) then
        tmp = c * ((a * j) - (z * b))
    else if (x <= 1.1d+40) then
        tmp = t_1 + (b * (t * i))
    else if ((x <= 1.1d+109) .or. (.not. (x <= 3.1d+146))) then
        tmp = t_2
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double t_2 = x * ((y * z) - (t * a));
	double tmp;
	if (x <= -3.9e+50) {
		tmp = t_2;
	} else if (x <= -3.5e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 1.1e+40) {
		tmp = t_1 + (b * (t * i));
	} else if ((x <= 1.1e+109) || !(x <= 3.1e+146)) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((a * c) - (y * i))
	t_2 = x * ((y * z) - (t * a))
	tmp = 0
	if x <= -3.9e+50:
		tmp = t_2
	elif x <= -3.5e-303:
		tmp = c * ((a * j) - (z * b))
	elif x <= 1.1e+40:
		tmp = t_1 + (b * (t * i))
	elif (x <= 1.1e+109) or not (x <= 3.1e+146):
		tmp = t_2
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	t_2 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	tmp = 0.0
	if (x <= -3.9e+50)
		tmp = t_2;
	elseif (x <= -3.5e-303)
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	elseif (x <= 1.1e+40)
		tmp = Float64(t_1 + Float64(b * Float64(t * i)));
	elseif ((x <= 1.1e+109) || !(x <= 3.1e+146))
		tmp = t_2;
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((a * c) - (y * i));
	t_2 = x * ((y * z) - (t * a));
	tmp = 0.0;
	if (x <= -3.9e+50)
		tmp = t_2;
	elseif (x <= -3.5e-303)
		tmp = c * ((a * j) - (z * b));
	elseif (x <= 1.1e+40)
		tmp = t_1 + (b * (t * i));
	elseif ((x <= 1.1e+109) || ~((x <= 3.1e+146)))
		tmp = t_2;
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -3.9e+50], t$95$2, If[LessEqual[x, -3.5e-303], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.1e+40], N[(t$95$1 + N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, 1.1e+109], N[Not[LessEqual[x, 3.1e+146]], $MachinePrecision]], t$95$2, t$95$1]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 11: 55.5% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(a \cdot c - y \cdot i\right)\\ t_2 := x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{if}\;x \leq -1.52 \cdot 10^{+50}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x \leq -4.5 \cdot 10^{-303}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{elif}\;x \leq 9.5 \cdot 10^{+39}:\\ \;\;\;\;t \cdot \left(b \cdot i\right) + t_1\\ \mathbf{elif}\;x \leq 2.2 \cdot 10^{+98} \lor \neg \left(x \leq 1.7 \cdot 10^{+147}\right):\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* a c) (* y i)))) (t_2 (* x (- (* y z) (* t a)))))
   (if (<= x -1.52e+50)
     t_2
     (if (<= x -4.5e-303)
       (* c (- (* a j) (* z b)))
       (if (<= x 9.5e+39)
         (+ (* t (* b i)) t_1)
         (if (or (<= x 2.2e+98) (not (<= x 1.7e+147))) t_2 t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double t_2 = x * ((y * z) - (t * a));
	double tmp;
	if (x <= -1.52e+50) {
		tmp = t_2;
	} else if (x <= -4.5e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 9.5e+39) {
		tmp = (t * (b * i)) + t_1;
	} else if ((x <= 2.2e+98) || !(x <= 1.7e+147)) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * ((a * c) - (y * i))
    t_2 = x * ((y * z) - (t * a))
    if (x <= (-1.52d+50)) then
        tmp = t_2
    else if (x <= (-4.5d-303)) then
        tmp = c * ((a * j) - (z * b))
    else if (x <= 9.5d+39) then
        tmp = (t * (b * i)) + t_1
    else if ((x <= 2.2d+98) .or. (.not. (x <= 1.7d+147))) then
        tmp = t_2
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((a * c) - (y * i));
	double t_2 = x * ((y * z) - (t * a));
	double tmp;
	if (x <= -1.52e+50) {
		tmp = t_2;
	} else if (x <= -4.5e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 9.5e+39) {
		tmp = (t * (b * i)) + t_1;
	} else if ((x <= 2.2e+98) || !(x <= 1.7e+147)) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((a * c) - (y * i))
	t_2 = x * ((y * z) - (t * a))
	tmp = 0
	if x <= -1.52e+50:
		tmp = t_2
	elif x <= -4.5e-303:
		tmp = c * ((a * j) - (z * b))
	elif x <= 9.5e+39:
		tmp = (t * (b * i)) + t_1
	elif (x <= 2.2e+98) or not (x <= 1.7e+147):
		tmp = t_2
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	t_2 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	tmp = 0.0
	if (x <= -1.52e+50)
		tmp = t_2;
	elseif (x <= -4.5e-303)
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	elseif (x <= 9.5e+39)
		tmp = Float64(Float64(t * Float64(b * i)) + t_1);
	elseif ((x <= 2.2e+98) || !(x <= 1.7e+147))
		tmp = t_2;
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((a * c) - (y * i));
	t_2 = x * ((y * z) - (t * a));
	tmp = 0.0;
	if (x <= -1.52e+50)
		tmp = t_2;
	elseif (x <= -4.5e-303)
		tmp = c * ((a * j) - (z * b));
	elseif (x <= 9.5e+39)
		tmp = (t * (b * i)) + t_1;
	elseif ((x <= 2.2e+98) || ~((x <= 1.7e+147)))
		tmp = t_2;
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.52e+50], t$95$2, If[LessEqual[x, -4.5e-303], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 9.5e+39], N[(N[(t * N[(b * i), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[Or[LessEqual[x, 2.2e+98], N[Not[LessEqual[x, 1.7e+147]], $MachinePrecision]], t$95$2, t$95$1]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 12: 58.0% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right) - j \cdot \left(y \cdot i\right)\\ \mathbf{if}\;x \leq -3.7 \cdot 10^{+28}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -4.3 \cdot 10^{-303}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{elif}\;x \leq 3.4 \cdot 10^{+35}:\\ \;\;\;\;t \cdot \left(b \cdot i\right) + j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (- (* x (- (* y z) (* t a))) (* j (* y i)))))
   (if (<= x -3.7e+28)
     t_1
     (if (<= x -4.3e-303)
       (* c (- (* a j) (* z b)))
       (if (<= x 3.4e+35) (+ (* t (* b i)) (* j (- (* a c) (* y i)))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = (x * ((y * z) - (t * a))) - (j * (y * i));
	double tmp;
	if (x <= -3.7e+28) {
		tmp = t_1;
	} else if (x <= -4.3e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 3.4e+35) {
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (x * ((y * z) - (t * a))) - (j * (y * i))
    if (x <= (-3.7d+28)) then
        tmp = t_1
    else if (x <= (-4.3d-303)) then
        tmp = c * ((a * j) - (z * b))
    else if (x <= 3.4d+35) then
        tmp = (t * (b * i)) + (j * ((a * c) - (y * i)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = (x * ((y * z) - (t * a))) - (j * (y * i));
	double tmp;
	if (x <= -3.7e+28) {
		tmp = t_1;
	} else if (x <= -4.3e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 3.4e+35) {
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = (x * ((y * z) - (t * a))) - (j * (y * i))
	tmp = 0
	if x <= -3.7e+28:
		tmp = t_1
	elif x <= -4.3e-303:
		tmp = c * ((a * j) - (z * b))
	elif x <= 3.4e+35:
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(j * Float64(y * i)))
	tmp = 0.0
	if (x <= -3.7e+28)
		tmp = t_1;
	elseif (x <= -4.3e-303)
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	elseif (x <= 3.4e+35)
		tmp = Float64(Float64(t * Float64(b * i)) + Float64(j * Float64(Float64(a * c) - Float64(y * i))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = (x * ((y * z) - (t * a))) - (j * (y * i));
	tmp = 0.0;
	if (x <= -3.7e+28)
		tmp = t_1;
	elseif (x <= -4.3e-303)
		tmp = c * ((a * j) - (z * b));
	elseif (x <= 3.4e+35)
		tmp = (t * (b * i)) + (j * ((a * c) - (y * i)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(j * N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -3.7e+28], t$95$1, If[LessEqual[x, -4.3e-303], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.4e+35], N[(N[(t * N[(b * i), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 13: 29.5% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(z \cdot \left(-b\right)\right)\\ t_2 := c \cdot \left(a \cdot j\right)\\ \mathbf{if}\;j \leq -2.4 \cdot 10^{-9}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq -7.5 \cdot 10^{-125}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(-x\right)\\ \mathbf{elif}\;j \leq -9.8 \cdot 10^{-200}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{-206}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{elif}\;j \leq 2.5 \cdot 10^{-194}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{-135}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 7.2 \cdot 10^{+99}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (* z (- b)))) (t_2 (* c (* a j))))
   (if (<= j -2.4e-9)
     t_2
     (if (<= j -7.5e-125)
       (* (* t a) (- x))
       (if (<= j -9.8e-200)
         t_1
         (if (<= j -8.5e-206)
           (* a (* x (- t)))
           (if (<= j 2.5e-194)
             (* y (* x z))
             (if (<= j 6.5e-135)
               t_1
               (if (<= j 7.2e+99) (* x (* y z)) t_2)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (z * -b);
	double t_2 = c * (a * j);
	double tmp;
	if (j <= -2.4e-9) {
		tmp = t_2;
	} else if (j <= -7.5e-125) {
		tmp = (t * a) * -x;
	} else if (j <= -9.8e-200) {
		tmp = t_1;
	} else if (j <= -8.5e-206) {
		tmp = a * (x * -t);
	} else if (j <= 2.5e-194) {
		tmp = y * (x * z);
	} else if (j <= 6.5e-135) {
		tmp = t_1;
	} else if (j <= 7.2e+99) {
		tmp = x * (y * z);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = c * (z * -b)
    t_2 = c * (a * j)
    if (j <= (-2.4d-9)) then
        tmp = t_2
    else if (j <= (-7.5d-125)) then
        tmp = (t * a) * -x
    else if (j <= (-9.8d-200)) then
        tmp = t_1
    else if (j <= (-8.5d-206)) then
        tmp = a * (x * -t)
    else if (j <= 2.5d-194) then
        tmp = y * (x * z)
    else if (j <= 6.5d-135) then
        tmp = t_1
    else if (j <= 7.2d+99) then
        tmp = x * (y * z)
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (z * -b);
	double t_2 = c * (a * j);
	double tmp;
	if (j <= -2.4e-9) {
		tmp = t_2;
	} else if (j <= -7.5e-125) {
		tmp = (t * a) * -x;
	} else if (j <= -9.8e-200) {
		tmp = t_1;
	} else if (j <= -8.5e-206) {
		tmp = a * (x * -t);
	} else if (j <= 2.5e-194) {
		tmp = y * (x * z);
	} else if (j <= 6.5e-135) {
		tmp = t_1;
	} else if (j <= 7.2e+99) {
		tmp = x * (y * z);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * (z * -b)
	t_2 = c * (a * j)
	tmp = 0
	if j <= -2.4e-9:
		tmp = t_2
	elif j <= -7.5e-125:
		tmp = (t * a) * -x
	elif j <= -9.8e-200:
		tmp = t_1
	elif j <= -8.5e-206:
		tmp = a * (x * -t)
	elif j <= 2.5e-194:
		tmp = y * (x * z)
	elif j <= 6.5e-135:
		tmp = t_1
	elif j <= 7.2e+99:
		tmp = x * (y * z)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(z * Float64(-b)))
	t_2 = Float64(c * Float64(a * j))
	tmp = 0.0
	if (j <= -2.4e-9)
		tmp = t_2;
	elseif (j <= -7.5e-125)
		tmp = Float64(Float64(t * a) * Float64(-x));
	elseif (j <= -9.8e-200)
		tmp = t_1;
	elseif (j <= -8.5e-206)
		tmp = Float64(a * Float64(x * Float64(-t)));
	elseif (j <= 2.5e-194)
		tmp = Float64(y * Float64(x * z));
	elseif (j <= 6.5e-135)
		tmp = t_1;
	elseif (j <= 7.2e+99)
		tmp = Float64(x * Float64(y * z));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * (z * -b);
	t_2 = c * (a * j);
	tmp = 0.0;
	if (j <= -2.4e-9)
		tmp = t_2;
	elseif (j <= -7.5e-125)
		tmp = (t * a) * -x;
	elseif (j <= -9.8e-200)
		tmp = t_1;
	elseif (j <= -8.5e-206)
		tmp = a * (x * -t);
	elseif (j <= 2.5e-194)
		tmp = y * (x * z);
	elseif (j <= 6.5e-135)
		tmp = t_1;
	elseif (j <= 7.2e+99)
		tmp = x * (y * z);
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.4e-9], t$95$2, If[LessEqual[j, -7.5e-125], N[(N[(t * a), $MachinePrecision] * (-x)), $MachinePrecision], If[LessEqual[j, -9.8e-200], t$95$1, If[LessEqual[j, -8.5e-206], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.5e-194], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.5e-135], t$95$1, If[LessEqual[j, 7.2e+99], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 14: 29.5% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(a \cdot j\right)\\ \mathbf{if}\;j \leq -2.2 \cdot 10^{-9}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -1.22 \cdot 10^{-124}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(-x\right)\\ \mathbf{elif}\;j \leq -1.2 \cdot 10^{-199}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \mathbf{elif}\;j \leq -1.25 \cdot 10^{-200}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-191}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \mathbf{elif}\;j \leq 1.8 \cdot 10^{-138}:\\ \;\;\;\;\left(b \cdot c\right) \cdot \left(-z\right)\\ \mathbf{elif}\;j \leq 3.4 \cdot 10^{+100}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (* a j))))
   (if (<= j -2.2e-9)
     t_1
     (if (<= j -1.22e-124)
       (* (* t a) (- x))
       (if (<= j -1.2e-199)
         (* c (* z (- b)))
         (if (<= j -1.25e-200)
           (* a (* x (- t)))
           (if (<= j 5e-191)
             (* y (* x z))
             (if (<= j 1.8e-138)
               (* (* b c) (- z))
               (if (<= j 3.4e+100) (* x (* y z)) t_1)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -2.2e-9) {
		tmp = t_1;
	} else if (j <= -1.22e-124) {
		tmp = (t * a) * -x;
	} else if (j <= -1.2e-199) {
		tmp = c * (z * -b);
	} else if (j <= -1.25e-200) {
		tmp = a * (x * -t);
	} else if (j <= 5e-191) {
		tmp = y * (x * z);
	} else if (j <= 1.8e-138) {
		tmp = (b * c) * -z;
	} else if (j <= 3.4e+100) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (a * j)
    if (j <= (-2.2d-9)) then
        tmp = t_1
    else if (j <= (-1.22d-124)) then
        tmp = (t * a) * -x
    else if (j <= (-1.2d-199)) then
        tmp = c * (z * -b)
    else if (j <= (-1.25d-200)) then
        tmp = a * (x * -t)
    else if (j <= 5d-191) then
        tmp = y * (x * z)
    else if (j <= 1.8d-138) then
        tmp = (b * c) * -z
    else if (j <= 3.4d+100) then
        tmp = x * (y * z)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -2.2e-9) {
		tmp = t_1;
	} else if (j <= -1.22e-124) {
		tmp = (t * a) * -x;
	} else if (j <= -1.2e-199) {
		tmp = c * (z * -b);
	} else if (j <= -1.25e-200) {
		tmp = a * (x * -t);
	} else if (j <= 5e-191) {
		tmp = y * (x * z);
	} else if (j <= 1.8e-138) {
		tmp = (b * c) * -z;
	} else if (j <= 3.4e+100) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * (a * j)
	tmp = 0
	if j <= -2.2e-9:
		tmp = t_1
	elif j <= -1.22e-124:
		tmp = (t * a) * -x
	elif j <= -1.2e-199:
		tmp = c * (z * -b)
	elif j <= -1.25e-200:
		tmp = a * (x * -t)
	elif j <= 5e-191:
		tmp = y * (x * z)
	elif j <= 1.8e-138:
		tmp = (b * c) * -z
	elif j <= 3.4e+100:
		tmp = x * (y * z)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(a * j))
	tmp = 0.0
	if (j <= -2.2e-9)
		tmp = t_1;
	elseif (j <= -1.22e-124)
		tmp = Float64(Float64(t * a) * Float64(-x));
	elseif (j <= -1.2e-199)
		tmp = Float64(c * Float64(z * Float64(-b)));
	elseif (j <= -1.25e-200)
		tmp = Float64(a * Float64(x * Float64(-t)));
	elseif (j <= 5e-191)
		tmp = Float64(y * Float64(x * z));
	elseif (j <= 1.8e-138)
		tmp = Float64(Float64(b * c) * Float64(-z));
	elseif (j <= 3.4e+100)
		tmp = Float64(x * Float64(y * z));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * (a * j);
	tmp = 0.0;
	if (j <= -2.2e-9)
		tmp = t_1;
	elseif (j <= -1.22e-124)
		tmp = (t * a) * -x;
	elseif (j <= -1.2e-199)
		tmp = c * (z * -b);
	elseif (j <= -1.25e-200)
		tmp = a * (x * -t);
	elseif (j <= 5e-191)
		tmp = y * (x * z);
	elseif (j <= 1.8e-138)
		tmp = (b * c) * -z;
	elseif (j <= 3.4e+100)
		tmp = x * (y * z);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.2e-9], t$95$1, If[LessEqual[j, -1.22e-124], N[(N[(t * a), $MachinePrecision] * (-x)), $MachinePrecision], If[LessEqual[j, -1.2e-199], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.25e-200], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5e-191], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.8e-138], N[(N[(b * c), $MachinePrecision] * (-z)), $MachinePrecision], If[LessEqual[j, 3.4e+100], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 15: 44.8% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(c \cdot j - x \cdot t\right)\\ t_2 := j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;x \leq -8 \cdot 10^{+257}:\\ \;\;\;\;z \cdot \left(x \cdot y\right)\\ \mathbf{elif}\;x \leq -3.2 \cdot 10^{+167}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -1.75 \cdot 10^{+67}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x \leq -3.2 \cdot 10^{-303}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{elif}\;x \leq 7.4 \cdot 10^{-29}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* c j) (* x t)))) (t_2 (* j (- (* a c) (* y i)))))
   (if (<= x -8e+257)
     (* z (* x y))
     (if (<= x -3.2e+167)
       t_1
       (if (<= x -1.75e+67)
         t_2
         (if (<= x -3.2e-303)
           (* c (- (* a j) (* z b)))
           (if (<= x 7.4e-29) t_2 t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((c * j) - (x * t));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (x <= -8e+257) {
		tmp = z * (x * y);
	} else if (x <= -3.2e+167) {
		tmp = t_1;
	} else if (x <= -1.75e+67) {
		tmp = t_2;
	} else if (x <= -3.2e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 7.4e-29) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = a * ((c * j) - (x * t))
    t_2 = j * ((a * c) - (y * i))
    if (x <= (-8d+257)) then
        tmp = z * (x * y)
    else if (x <= (-3.2d+167)) then
        tmp = t_1
    else if (x <= (-1.75d+67)) then
        tmp = t_2
    else if (x <= (-3.2d-303)) then
        tmp = c * ((a * j) - (z * b))
    else if (x <= 7.4d-29) then
        tmp = t_2
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((c * j) - (x * t));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (x <= -8e+257) {
		tmp = z * (x * y);
	} else if (x <= -3.2e+167) {
		tmp = t_1;
	} else if (x <= -1.75e+67) {
		tmp = t_2;
	} else if (x <= -3.2e-303) {
		tmp = c * ((a * j) - (z * b));
	} else if (x <= 7.4e-29) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((c * j) - (x * t))
	t_2 = j * ((a * c) - (y * i))
	tmp = 0
	if x <= -8e+257:
		tmp = z * (x * y)
	elif x <= -3.2e+167:
		tmp = t_1
	elif x <= -1.75e+67:
		tmp = t_2
	elif x <= -3.2e-303:
		tmp = c * ((a * j) - (z * b))
	elif x <= 7.4e-29:
		tmp = t_2
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	t_2 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	tmp = 0.0
	if (x <= -8e+257)
		tmp = Float64(z * Float64(x * y));
	elseif (x <= -3.2e+167)
		tmp = t_1;
	elseif (x <= -1.75e+67)
		tmp = t_2;
	elseif (x <= -3.2e-303)
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	elseif (x <= 7.4e-29)
		tmp = t_2;
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = a * ((c * j) - (x * t));
	t_2 = j * ((a * c) - (y * i));
	tmp = 0.0;
	if (x <= -8e+257)
		tmp = z * (x * y);
	elseif (x <= -3.2e+167)
		tmp = t_1;
	elseif (x <= -1.75e+67)
		tmp = t_2;
	elseif (x <= -3.2e-303)
		tmp = c * ((a * j) - (z * b));
	elseif (x <= 7.4e-29)
		tmp = t_2;
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -8e+257], N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -3.2e+167], t$95$1, If[LessEqual[x, -1.75e+67], t$95$2, If[LessEqual[x, -3.2e-303], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 7.4e-29], t$95$2, t$95$1]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 16: 50.9% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -1.35 \cdot 10^{-57}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 1.8 \cdot 10^{-247}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 2.45 \cdot 10^{-120}:\\ \;\;\;\;z \cdot \left(x \cdot y - b \cdot c\right)\\ \mathbf{elif}\;j \leq 2.25 \cdot 10^{-107}:\\ \;\;\;\;i \cdot \left(t \cdot b\right)\\ \mathbf{elif}\;j \leq 1.18 \cdot 10^{+104}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* j (- (* a c) (* y i)))))
   (if (<= j -1.35e-57)
     t_2
     (if (<= j 1.8e-247)
       t_1
       (if (<= j 2.45e-120)
         (* z (- (* x y) (* b c)))
         (if (<= j 2.25e-107) (* i (* t b)) (if (<= j 1.18e+104) t_1 t_2)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -1.35e-57) {
		tmp = t_2;
	} else if (j <= 1.8e-247) {
		tmp = t_1;
	} else if (j <= 2.45e-120) {
		tmp = z * ((x * y) - (b * c));
	} else if (j <= 2.25e-107) {
		tmp = i * (t * b);
	} else if (j <= 1.18e+104) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * ((y * z) - (t * a))
    t_2 = j * ((a * c) - (y * i))
    if (j <= (-1.35d-57)) then
        tmp = t_2
    else if (j <= 1.8d-247) then
        tmp = t_1
    else if (j <= 2.45d-120) then
        tmp = z * ((x * y) - (b * c))
    else if (j <= 2.25d-107) then
        tmp = i * (t * b)
    else if (j <= 1.18d+104) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -1.35e-57) {
		tmp = t_2;
	} else if (j <= 1.8e-247) {
		tmp = t_1;
	} else if (j <= 2.45e-120) {
		tmp = z * ((x * y) - (b * c));
	} else if (j <= 2.25e-107) {
		tmp = i * (t * b);
	} else if (j <= 1.18e+104) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * ((y * z) - (t * a))
	t_2 = j * ((a * c) - (y * i))
	tmp = 0
	if j <= -1.35e-57:
		tmp = t_2
	elif j <= 1.8e-247:
		tmp = t_1
	elif j <= 2.45e-120:
		tmp = z * ((x * y) - (b * c))
	elif j <= 2.25e-107:
		tmp = i * (t * b)
	elif j <= 1.18e+104:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	t_2 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -1.35e-57)
		tmp = t_2;
	elseif (j <= 1.8e-247)
		tmp = t_1;
	elseif (j <= 2.45e-120)
		tmp = Float64(z * Float64(Float64(x * y) - Float64(b * c)));
	elseif (j <= 2.25e-107)
		tmp = Float64(i * Float64(t * b));
	elseif (j <= 1.18e+104)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((y * z) - (t * a));
	t_2 = j * ((a * c) - (y * i));
	tmp = 0.0;
	if (j <= -1.35e-57)
		tmp = t_2;
	elseif (j <= 1.8e-247)
		tmp = t_1;
	elseif (j <= 2.45e-120)
		tmp = z * ((x * y) - (b * c));
	elseif (j <= 2.25e-107)
		tmp = i * (t * b);
	elseif (j <= 1.18e+104)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.35e-57], t$95$2, If[LessEqual[j, 1.8e-247], t$95$1, If[LessEqual[j, 2.45e-120], N[(z * N[(N[(x * y), $MachinePrecision] - N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.25e-107], N[(i * N[(t * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.18e+104], t$95$1, t$95$2]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 17: 50.8% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -2.05 \cdot 10^{-57}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 2.35 \cdot 10^{-120}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 6.6 \cdot 10^{-107}:\\ \;\;\;\;i \cdot \left(t \cdot b\right)\\ \mathbf{elif}\;j \leq 6.9 \cdot 10^{+103}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* j (- (* a c) (* y i)))))
   (if (<= j -2.05e-57)
     t_2
     (if (<= j 2.35e-120)
       t_1
       (if (<= j 6.6e-107) (* i (* t b)) (if (<= j 6.9e+103) t_1 t_2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -2.05e-57) {
		tmp = t_2;
	} else if (j <= 2.35e-120) {
		tmp = t_1;
	} else if (j <= 6.6e-107) {
		tmp = i * (t * b);
	} else if (j <= 6.9e+103) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * ((y * z) - (t * a))
    t_2 = j * ((a * c) - (y * i))
    if (j <= (-2.05d-57)) then
        tmp = t_2
    else if (j <= 2.35d-120) then
        tmp = t_1
    else if (j <= 6.6d-107) then
        tmp = i * (t * b)
    else if (j <= 6.9d+103) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -2.05e-57) {
		tmp = t_2;
	} else if (j <= 2.35e-120) {
		tmp = t_1;
	} else if (j <= 6.6e-107) {
		tmp = i * (t * b);
	} else if (j <= 6.9e+103) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * ((y * z) - (t * a))
	t_2 = j * ((a * c) - (y * i))
	tmp = 0
	if j <= -2.05e-57:
		tmp = t_2
	elif j <= 2.35e-120:
		tmp = t_1
	elif j <= 6.6e-107:
		tmp = i * (t * b)
	elif j <= 6.9e+103:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	t_2 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -2.05e-57)
		tmp = t_2;
	elseif (j <= 2.35e-120)
		tmp = t_1;
	elseif (j <= 6.6e-107)
		tmp = Float64(i * Float64(t * b));
	elseif (j <= 6.9e+103)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((y * z) - (t * a));
	t_2 = j * ((a * c) - (y * i));
	tmp = 0.0;
	if (j <= -2.05e-57)
		tmp = t_2;
	elseif (j <= 2.35e-120)
		tmp = t_1;
	elseif (j <= 6.6e-107)
		tmp = i * (t * b);
	elseif (j <= 6.9e+103)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.05e-57], t$95$2, If[LessEqual[j, 2.35e-120], t$95$1, If[LessEqual[j, 6.6e-107], N[(i * N[(t * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.9e+103], t$95$1, t$95$2]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 18: 29.7% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(a \cdot j\right)\\ \mathbf{if}\;j \leq -1.7 \cdot 10^{-10}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -9 \cdot 10^{-208}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{-191}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \mathbf{elif}\;j \leq 1.32 \cdot 10^{-134}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \mathbf{elif}\;j \leq 3.2 \cdot 10^{+98}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (* a j))))
   (if (<= j -1.7e-10)
     t_1
     (if (<= j -9e-208)
       (* a (* x (- t)))
       (if (<= j 1.5e-191)
         (* y (* x z))
         (if (<= j 1.32e-134)
           (* c (* z (- b)))
           (if (<= j 3.2e+98) (* x (* y z)) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -1.7e-10) {
		tmp = t_1;
	} else if (j <= -9e-208) {
		tmp = a * (x * -t);
	} else if (j <= 1.5e-191) {
		tmp = y * (x * z);
	} else if (j <= 1.32e-134) {
		tmp = c * (z * -b);
	} else if (j <= 3.2e+98) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (a * j)
    if (j <= (-1.7d-10)) then
        tmp = t_1
    else if (j <= (-9d-208)) then
        tmp = a * (x * -t)
    else if (j <= 1.5d-191) then
        tmp = y * (x * z)
    else if (j <= 1.32d-134) then
        tmp = c * (z * -b)
    else if (j <= 3.2d+98) then
        tmp = x * (y * z)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -1.7e-10) {
		tmp = t_1;
	} else if (j <= -9e-208) {
		tmp = a * (x * -t);
	} else if (j <= 1.5e-191) {
		tmp = y * (x * z);
	} else if (j <= 1.32e-134) {
		tmp = c * (z * -b);
	} else if (j <= 3.2e+98) {
		tmp = x * (y * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * (a * j)
	tmp = 0
	if j <= -1.7e-10:
		tmp = t_1
	elif j <= -9e-208:
		tmp = a * (x * -t)
	elif j <= 1.5e-191:
		tmp = y * (x * z)
	elif j <= 1.32e-134:
		tmp = c * (z * -b)
	elif j <= 3.2e+98:
		tmp = x * (y * z)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(a * j))
	tmp = 0.0
	if (j <= -1.7e-10)
		tmp = t_1;
	elseif (j <= -9e-208)
		tmp = Float64(a * Float64(x * Float64(-t)));
	elseif (j <= 1.5e-191)
		tmp = Float64(y * Float64(x * z));
	elseif (j <= 1.32e-134)
		tmp = Float64(c * Float64(z * Float64(-b)));
	elseif (j <= 3.2e+98)
		tmp = Float64(x * Float64(y * z));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * (a * j);
	tmp = 0.0;
	if (j <= -1.7e-10)
		tmp = t_1;
	elseif (j <= -9e-208)
		tmp = a * (x * -t);
	elseif (j <= 1.5e-191)
		tmp = y * (x * z);
	elseif (j <= 1.32e-134)
		tmp = c * (z * -b);
	elseif (j <= 3.2e+98)
		tmp = x * (y * z);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.7e-10], t$95$1, If[LessEqual[j, -9e-208], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.5e-191], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.32e-134], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.2e+98], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 19: 29.6% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -2.2 \cdot 10^{+33}:\\ \;\;\;\;i \cdot \left(t \cdot b\right)\\ \mathbf{elif}\;t \leq -5.8 \cdot 10^{-116}:\\ \;\;\;\;b \cdot \left(c \cdot \left(-z\right)\right)\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{-273}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{+122}:\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(-x\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= t -2.2e+33)
   (* i (* t b))
   (if (<= t -5.8e-116)
     (* b (* c (- z)))
     (if (<= t 1.4e-273)
       (* x (* y z))
       (if (<= t 3.7e+122) (* c (* a j)) (* (* t a) (- x)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -2.2e+33) {
		tmp = i * (t * b);
	} else if (t <= -5.8e-116) {
		tmp = b * (c * -z);
	} else if (t <= 1.4e-273) {
		tmp = x * (y * z);
	} else if (t <= 3.7e+122) {
		tmp = c * (a * j);
	} else {
		tmp = (t * a) * -x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (t <= (-2.2d+33)) then
        tmp = i * (t * b)
    else if (t <= (-5.8d-116)) then
        tmp = b * (c * -z)
    else if (t <= 1.4d-273) then
        tmp = x * (y * z)
    else if (t <= 3.7d+122) then
        tmp = c * (a * j)
    else
        tmp = (t * a) * -x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -2.2e+33) {
		tmp = i * (t * b);
	} else if (t <= -5.8e-116) {
		tmp = b * (c * -z);
	} else if (t <= 1.4e-273) {
		tmp = x * (y * z);
	} else if (t <= 3.7e+122) {
		tmp = c * (a * j);
	} else {
		tmp = (t * a) * -x;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if t <= -2.2e+33:
		tmp = i * (t * b)
	elif t <= -5.8e-116:
		tmp = b * (c * -z)
	elif t <= 1.4e-273:
		tmp = x * (y * z)
	elif t <= 3.7e+122:
		tmp = c * (a * j)
	else:
		tmp = (t * a) * -x
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (t <= -2.2e+33)
		tmp = Float64(i * Float64(t * b));
	elseif (t <= -5.8e-116)
		tmp = Float64(b * Float64(c * Float64(-z)));
	elseif (t <= 1.4e-273)
		tmp = Float64(x * Float64(y * z));
	elseif (t <= 3.7e+122)
		tmp = Float64(c * Float64(a * j));
	else
		tmp = Float64(Float64(t * a) * Float64(-x));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (t <= -2.2e+33)
		tmp = i * (t * b);
	elseif (t <= -5.8e-116)
		tmp = b * (c * -z);
	elseif (t <= 1.4e-273)
		tmp = x * (y * z);
	elseif (t <= 3.7e+122)
		tmp = c * (a * j);
	else
		tmp = (t * a) * -x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[t, -2.2e+33], N[(i * N[(t * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.8e-116], N[(b * N[(c * (-z)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.4e-273], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.7e+122], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], N[(N[(t * a), $MachinePrecision] * (-x)), $MachinePrecision]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 20: 45.1% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -2.3 \cdot 10^{+22} \lor \neg \left(a \leq 9.2 \cdot 10^{+51}\right):\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= a -2.3e+22) (not (<= a 9.2e+51)))
   (* a (- (* c j) (* x t)))
   (* c (- (* a j) (* z b)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((a <= -2.3e+22) || !(a <= 9.2e+51)) {
		tmp = a * ((c * j) - (x * t));
	} else {
		tmp = c * ((a * j) - (z * b));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((a <= (-2.3d+22)) .or. (.not. (a <= 9.2d+51))) then
        tmp = a * ((c * j) - (x * t))
    else
        tmp = c * ((a * j) - (z * b))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((a <= -2.3e+22) || !(a <= 9.2e+51)) {
		tmp = a * ((c * j) - (x * t));
	} else {
		tmp = c * ((a * j) - (z * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (a <= -2.3e+22) or not (a <= 9.2e+51):
		tmp = a * ((c * j) - (x * t))
	else:
		tmp = c * ((a * j) - (z * b))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((a <= -2.3e+22) || !(a <= 9.2e+51))
		tmp = Float64(a * Float64(Float64(c * j) - Float64(x * t)));
	else
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((a <= -2.3e+22) || ~((a <= 9.2e+51)))
		tmp = a * ((c * j) - (x * t));
	else
		tmp = c * ((a * j) - (z * b));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[a, -2.3e+22], N[Not[LessEqual[a, 9.2e+51]], $MachinePrecision]], N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 21: 41.5% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -1.65 \cdot 10^{+98}:\\ \;\;\;\;i \cdot \left(t \cdot b\right)\\ \mathbf{elif}\;b \leq 5.2 \cdot 10^{+104}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= b -1.65e+98)
   (* i (* t b))
   (if (<= b 5.2e+104) (* a (- (* c j) (* x t))) (* c (* z (- b))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (b <= -1.65e+98) {
		tmp = i * (t * b);
	} else if (b <= 5.2e+104) {
		tmp = a * ((c * j) - (x * t));
	} else {
		tmp = c * (z * -b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (b <= (-1.65d+98)) then
        tmp = i * (t * b)
    else if (b <= 5.2d+104) then
        tmp = a * ((c * j) - (x * t))
    else
        tmp = c * (z * -b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (b <= -1.65e+98) {
		tmp = i * (t * b);
	} else if (b <= 5.2e+104) {
		tmp = a * ((c * j) - (x * t));
	} else {
		tmp = c * (z * -b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if b <= -1.65e+98:
		tmp = i * (t * b)
	elif b <= 5.2e+104:
		tmp = a * ((c * j) - (x * t))
	else:
		tmp = c * (z * -b)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (b <= -1.65e+98)
		tmp = Float64(i * Float64(t * b));
	elseif (b <= 5.2e+104)
		tmp = Float64(a * Float64(Float64(c * j) - Float64(x * t)));
	else
		tmp = Float64(c * Float64(z * Float64(-b)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (b <= -1.65e+98)
		tmp = i * (t * b);
	elseif (b <= 5.2e+104)
		tmp = a * ((c * j) - (x * t));
	else
		tmp = c * (z * -b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[b, -1.65e+98], N[(i * N[(t * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 5.2e+104], N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 22: 29.9% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(a \cdot j\right)\\ \mathbf{if}\;j \leq -1.25 \cdot 10^{-9}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -5.7 \cdot 10^{-207}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{elif}\;j \leq 5.5 \cdot 10^{+99}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (* a j))))
   (if (<= j -1.25e-9)
     t_1
     (if (<= j -5.7e-207)
       (* a (* x (- t)))
       (if (<= j 5.5e+99) (* y (* x z)) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -1.25e-9) {
		tmp = t_1;
	} else if (j <= -5.7e-207) {
		tmp = a * (x * -t);
	} else if (j <= 5.5e+99) {
		tmp = y * (x * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (a * j)
    if (j <= (-1.25d-9)) then
        tmp = t_1
    else if (j <= (-5.7d-207)) then
        tmp = a * (x * -t)
    else if (j <= 5.5d+99) then
        tmp = y * (x * z)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * (a * j);
	double tmp;
	if (j <= -1.25e-9) {
		tmp = t_1;
	} else if (j <= -5.7e-207) {
		tmp = a * (x * -t);
	} else if (j <= 5.5e+99) {
		tmp = y * (x * z);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * (a * j)
	tmp = 0
	if j <= -1.25e-9:
		tmp = t_1
	elif j <= -5.7e-207:
		tmp = a * (x * -t)
	elif j <= 5.5e+99:
		tmp = y * (x * z)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(a * j))
	tmp = 0.0
	if (j <= -1.25e-9)
		tmp = t_1;
	elseif (j <= -5.7e-207)
		tmp = Float64(a * Float64(x * Float64(-t)));
	elseif (j <= 5.5e+99)
		tmp = Float64(y * Float64(x * z));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * (a * j);
	tmp = 0.0;
	if (j <= -1.25e-9)
		tmp = t_1;
	elseif (j <= -5.7e-207)
		tmp = a * (x * -t);
	elseif (j <= 5.5e+99)
		tmp = y * (x * z);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.25e-9], t$95$1, If[LessEqual[j, -5.7e-207], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5.5e+99], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 23: 28.6% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.3 \cdot 10^{+95} \lor \neg \left(b \leq 2.3 \cdot 10^{+78}\right):\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(c \cdot j\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= b -4.3e+95) (not (<= b 2.3e+78))) (* b (* t i)) (* a (* c j))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((b <= -4.3e+95) || !(b <= 2.3e+78)) {
		tmp = b * (t * i);
	} else {
		tmp = a * (c * j);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((b <= (-4.3d+95)) .or. (.not. (b <= 2.3d+78))) then
        tmp = b * (t * i)
    else
        tmp = a * (c * j)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((b <= -4.3e+95) || !(b <= 2.3e+78)) {
		tmp = b * (t * i);
	} else {
		tmp = a * (c * j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (b <= -4.3e+95) or not (b <= 2.3e+78):
		tmp = b * (t * i)
	else:
		tmp = a * (c * j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((b <= -4.3e+95) || !(b <= 2.3e+78))
		tmp = Float64(b * Float64(t * i));
	else
		tmp = Float64(a * Float64(c * j));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((b <= -4.3e+95) || ~((b <= 2.3e+78)))
		tmp = b * (t * i);
	else
		tmp = a * (c * j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[b, -4.3e+95], N[Not[LessEqual[b, 2.3e+78]], $MachinePrecision]], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 24: 29.1% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -4.2 \cdot 10^{-10} \lor \neg \left(j \leq 2.95 \cdot 10^{+79}\right):\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= j -4.2e-10) (not (<= j 2.95e+79))) (* c (* a j)) (* b (* t i))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -4.2e-10) || !(j <= 2.95e+79)) {
		tmp = c * (a * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((j <= (-4.2d-10)) .or. (.not. (j <= 2.95d+79))) then
        tmp = c * (a * j)
    else
        tmp = b * (t * i)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -4.2e-10) || !(j <= 2.95e+79)) {
		tmp = c * (a * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (j <= -4.2e-10) or not (j <= 2.95e+79):
		tmp = c * (a * j)
	else:
		tmp = b * (t * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((j <= -4.2e-10) || !(j <= 2.95e+79))
		tmp = Float64(c * Float64(a * j));
	else
		tmp = Float64(b * Float64(t * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((j <= -4.2e-10) || ~((j <= 2.95e+79)))
		tmp = c * (a * j);
	else
		tmp = b * (t * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[j, -4.2e-10], N[Not[LessEqual[j, 2.95e+79]], $MachinePrecision]], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 25: 29.0% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -4 \cdot 10^{-9} \lor \neg \left(j \leq 3.8 \cdot 10^{+99}\right):\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= j -4e-9) (not (<= j 3.8e+99))) (* c (* a j)) (* x (* y z))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -4e-9) || !(j <= 3.8e+99)) {
		tmp = c * (a * j);
	} else {
		tmp = x * (y * z);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((j <= (-4d-9)) .or. (.not. (j <= 3.8d+99))) then
        tmp = c * (a * j)
    else
        tmp = x * (y * z)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -4e-9) || !(j <= 3.8e+99)) {
		tmp = c * (a * j);
	} else {
		tmp = x * (y * z);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (j <= -4e-9) or not (j <= 3.8e+99):
		tmp = c * (a * j)
	else:
		tmp = x * (y * z)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((j <= -4e-9) || !(j <= 3.8e+99))
		tmp = Float64(c * Float64(a * j));
	else
		tmp = Float64(x * Float64(y * z));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((j <= -4e-9) || ~((j <= 3.8e+99)))
		tmp = c * (a * j);
	else
		tmp = x * (y * z);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[j, -4e-9], N[Not[LessEqual[j, 3.8e+99]], $MachinePrecision]], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 26: 29.7% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -8.5 \cdot 10^{-10} \lor \neg \left(j \leq 3.2 \cdot 10^{+98}\right):\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= j -8.5e-10) (not (<= j 3.2e+98))) (* c (* a j)) (* y (* x z))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -8.5e-10) || !(j <= 3.2e+98)) {
		tmp = c * (a * j);
	} else {
		tmp = y * (x * z);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((j <= (-8.5d-10)) .or. (.not. (j <= 3.2d+98))) then
        tmp = c * (a * j)
    else
        tmp = y * (x * z)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -8.5e-10) || !(j <= 3.2e+98)) {
		tmp = c * (a * j);
	} else {
		tmp = y * (x * z);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (j <= -8.5e-10) or not (j <= 3.2e+98):
		tmp = c * (a * j)
	else:
		tmp = y * (x * z)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((j <= -8.5e-10) || !(j <= 3.2e+98))
		tmp = Float64(c * Float64(a * j));
	else
		tmp = Float64(y * Float64(x * z));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((j <= -8.5e-10) || ~((j <= 3.2e+98)))
		tmp = c * (a * j);
	else
		tmp = y * (x * z);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[j, -8.5e-10], N[Not[LessEqual[j, 3.2e+98]], $MachinePrecision]], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 27: 21.5% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(c \cdot j\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j) :precision binary64 (* a (* c j)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return a * (c * j);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    code = a * (c * j)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return a * (c * j);
}

Python

def code(x, y, z, t, a, b, c, i, j):
	return a * (c * j)

Julia

function code(x, y, z, t, a, b, c, i, j)
	return Float64(a * Float64(c * j))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = a * (c * j);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Developer target: 58.7% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(c \cdot a - y \cdot i\right)\\ t_2 := \left(x \cdot \left(y \cdot z - t \cdot a\right) - \frac{b \cdot \left({\left(c \cdot z\right)}^{2} - {\left(t \cdot i\right)}^{2}\right)}{c \cdot z + t \cdot i}\right) + t_1\\ \mathbf{if}\;x < -1.469694296777705 \cdot 10^{-64}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x < 3.2113527362226803 \cdot 10^{-147}:\\ \;\;\;\;\left(b \cdot i - x \cdot a\right) \cdot t - \left(z \cdot \left(c \cdot b\right) - t_1\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* c a) (* y i))))
        (t_2
         (+
          (-
           (* x (- (* y z) (* t a)))
           (/
            (* b (- (pow (* c z) 2.0) (pow (* t i) 2.0)))
            (+ (* c z) (* t i))))
          t_1)))
   (if (< x -1.469694296777705e-64)
     t_2
     (if (< x 3.2113527362226803e-147)
       (- (* (- (* b i) (* x a)) t) (- (* z (* c b)) t_1))
       t_2))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((c * a) - (y * i));
	double t_2 = ((x * ((y * z) - (t * a))) - ((b * (pow((c * z), 2.0) - pow((t * i), 2.0))) / ((c * z) + (t * i)))) + t_1;
	double tmp;
	if (x < -1.469694296777705e-64) {
		tmp = t_2;
	} else if (x < 3.2113527362226803e-147) {
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - t_1);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * ((c * a) - (y * i))
    t_2 = ((x * ((y * z) - (t * a))) - ((b * (((c * z) ** 2.0d0) - ((t * i) ** 2.0d0))) / ((c * z) + (t * i)))) + t_1
    if (x < (-1.469694296777705d-64)) then
        tmp = t_2
    else if (x < 3.2113527362226803d-147) then
        tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - t_1)
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((c * a) - (y * i));
	double t_2 = ((x * ((y * z) - (t * a))) - ((b * (Math.pow((c * z), 2.0) - Math.pow((t * i), 2.0))) / ((c * z) + (t * i)))) + t_1;
	double tmp;
	if (x < -1.469694296777705e-64) {
		tmp = t_2;
	} else if (x < 3.2113527362226803e-147) {
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - t_1);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((c * a) - (y * i))
	t_2 = ((x * ((y * z) - (t * a))) - ((b * (math.pow((c * z), 2.0) - math.pow((t * i), 2.0))) / ((c * z) + (t * i)))) + t_1
	tmp = 0
	if x < -1.469694296777705e-64:
		tmp = t_2
	elif x < 3.2113527362226803e-147:
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - t_1)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(c * a) - Float64(y * i)))
	t_2 = Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(Float64(b * Float64((Float64(c * z) ^ 2.0) - (Float64(t * i) ^ 2.0))) / Float64(Float64(c * z) + Float64(t * i)))) + t_1)
	tmp = 0.0
	if (x < -1.469694296777705e-64)
		tmp = t_2;
	elseif (x < 3.2113527362226803e-147)
		tmp = Float64(Float64(Float64(Float64(b * i) - Float64(x * a)) * t) - Float64(Float64(z * Float64(c * b)) - t_1));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((c * a) - (y * i));
	t_2 = ((x * ((y * z) - (t * a))) - ((b * (((c * z) ^ 2.0) - ((t * i) ^ 2.0))) / ((c * z) + (t * i)))) + t_1;
	tmp = 0.0;
	if (x < -1.469694296777705e-64)
		tmp = t_2;
	elseif (x < 3.2113527362226803e-147)
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - t_1);
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(c * a), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(b * N[(N[Power[N[(c * z), $MachinePrecision], 2.0], $MachinePrecision] - N[Power[N[(t * i), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(c * z), $MachinePrecision] + N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, If[Less[x, -1.469694296777705e-64], t$95$2, If[Less[x, 3.2113527362226803e-147], N[(N[(N[(N[(b * i), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision] * t), $MachinePrecision] - N[(N[(z * N[(c * b), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]), $MachinePrecision], t$95$2]]]]

Reproduce

herbie shell --seed 2023350 
(FPCore (x y z t a b c i j)
  :name "Data.Colour.Matrix:determinant from colour-2.3.3, A"
  :precision binary64

  :herbie-target
  (if (< x -1.469694296777705e-64) (+ (- (* x (- (* y z) (* t a))) (/ (* b (- (pow (* c z) 2.0) (pow (* t i) 2.0))) (+ (* c z) (* t i)))) (* j (- (* c a) (* y i)))) (if (< x 3.2113527362226803e-147) (- (* (- (* b i) (* x a)) t) (- (* z (* c b)) (* j (- (* c a) (* y i))))) (+ (- (* x (- (* y z) (* t a))) (/ (* b (- (pow (* c z) 2.0) (pow (* t i) 2.0))) (+ (* c z) (* t i)))) (* j (- (* c a) (* y i))))))

  (+ (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* t i)))) (* j (- (* c a) (* y i)))))